Bibliographic record
Abstract
Purpose This paper seeks to provide recent case study evidence for the remarkable growth of electronic resources in academic library collections and to analyze growth patterns and impacts. Design/methodology/approach A case study reviewed electronic resources growth at the University of Saskatchewan Library over a 12‐year time series, from 1996‐1997 to 2007‐2008. The researcher collected data from the library's databases A‐Z lists over the time series, compiled statistics and growth rates for both net holdings and new acquisitions, then analyzed and contextualized the results. Findings The study reveals three electronic resources growth or development stages corresponding to advances in electronic resource types – i.e. bibliographic, full text and reference – and a pattern of sustained rapid growth. It was found that growth doubled within the last four years of the time series, with ±100 resources being added annually in the same period. Both internal and external events impacted on growth. Just as internal and external events contribute to the growth of electronic resources, new events such as economic decline may contribute to growth decline. Research limitations/implications While the study is limited to a single academic library case, it has applications to similar academic library profiles across North America, where sustained rapid growth has had a significant impact on reference workers and researchers. Practical implications This research provides a case study for describing electronic resources growth in academic libraries. The data and findings may help support funding increases, and an understanding of the extent of growth and its impact on reference workers and researchers. Originality/value Although generalizations from one case study cannot be made, this study of electronic resources growth and its implications substantiates the general conviction that overwhelming growth has occurred and that the consequences for library services and systems is considerable. The paper applies the concept of growth or development stages: bibliographic, full text and reference, to describe the evolution of electronic resources in an academic library.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.015 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".